Soil management of sugarcane fields affecting CO2 fluxes

Rose Luiza Moraes Tavares Diego Silva Siqueira Alan Rodrigo Panosso Guilherme Adalberto Ferreira Castioni Zigomar Menezes de Souza Newton La Scala Jr.About the authors

ABSTRACT

The harvesting system of green sugarcane, characterized by mechanized harvesting and no crop burning, affects soil quality by increasing the remaining straw left on the soil surface after harvesting, thus, contributing to the improvement of physical, chemical, and microbiological soil attributes, influencing CO2 fluxes. This study aimed to evaluate CO2 fluxes and their relation to soil properties in sugarcane crops under different harvesting managements: burned (B), Green harvesting for 5 years (G-5) and Green harvesting for ten years (G-10). For this, a 1 ha sampling grid with 30 points was installed in each area, all located in the Northeast of São Paulo State, Brazil. In each point, CO2 fluxes were measured and the soil was sampled to analyze the microbial biomass, physical (soil moisture and temperature, mean weight diameter, bulk density, clay, macroporosity and microporosity) and chemical characterization (pH, organic C, base saturation and P). The CO2 fluxes were divided into four quantitative criteria: high, moderate, low and very low from the Statistical Division (mean, first quartile, median and third quartile) and the other data were classified according this criterion. The Principal Component Analysis (PCA) was used to identify the main soil attributes that influence CO2 fluxes. The results showed that G-10 CO2 fluxes were 28 and 41 % higher than those in the G-5 and B treatments, respectively. The PCA analysis showed that macroporosity was the main soil attribute that influenced the high CO2 fluxes.

Keywords:
Sacharum officinarum; principal component analysis; porosity; biomass

Introduction

The practice of burning sugarcane residues prior to harvesting aims to facilitate manual cutting, but the temperature during sugarcane burning is around 160-200 °C on the soil surface, causing nutrients loss by volatilization such as phosphorus, sulfur and nitrogen (Ball et al., 1993Ball, B.C.; Tiessen, H.; Stewart, J.W.B.; Salcedo, I.H.; Sampaio, E.V.S.B. 1993. Residue management effects on sugarcane yield and soil properties in northeastern Brazil. Agronomy Journal 85: 1004-1008.) and may lead to a great decline in soil C stocks (Song et al., 2013Song, Z.; Yuan, H.; Kimberley, M.O.; Jiang, H.; Zhou, G.; Wang, H. 2013. Soil CO2 flux dynamics in the two main plantation forest types in subtropical China. Science of the Total Environment 444: 363-368.). The “harvesting of green sugarcane” is a system without burning that leaves biomass waste in the field after harvesting, positively influencing soil quality by increasing the deposited residual straw (mean 10 to 30 Mg ha−1) allowing carbon accumulation in the soil, which implies in a positive CO2 balance as described by Razafimbelo et al. (2006)Razafimbelo, T.; Barthès, B.; Larré-Larrouy, M.C.; De Luca, E.F.; Laurent, J.Y.; Cerri, C.C.; Feller, C. 2006. Effect of sugarcane residue management (mulching versus burning) on OM in a clayey Oxisol from southern Brazil. Agriculture, Ecosystems and Environment 115: 285-289..

Soil CO2 fluxes from areas of sugarcane cultivation were studied by Brito et al. (2009)Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83. that found greater fluxes in areas with greater soil macroporosity. Panosso et al. (2009)Panosso, A.R.; Marques Júnior, J.; Pereira, G.T.; La Scala, N. 2009. Spatial and temporal variability of soil CO2 emission in a sugarcane area under green and Slash-and-burn managements. Soil and Tillage Research 105: 275-282. compared the soil CO2 in pre-harvesting burned crop with a green harvesting system and found that soil cations were the main soil attribute to explain the CO2 fluxes mainly in the burned area.

Soil CO2 fluxes result from physical and biological processes that affect CO2 production and transport from the soil to the atmosphere. In addition, production is related to root respiration and the action of microorganisms during OM decomposition (Jenkinson and Ladd, 1981Jenkinson, D.S.; Ladd, J.N. 1981. Microbial biomass in soil: measurement and turnover. Soil Biology and Biochemistry 5: 415-471.; Brito et al., 2009Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83.). Transport of soil gases is influenced by the physical structure parameters, such as porosity, which drive the gas flow. Saturation of soil pores also determines CO2 fluxes. According to the literature, the main soil attributes that influence CO2 fluxes include temperature and content of soil water (Xu and Qi, 2001Xu, M.; Qi, Y. 2001. Soil-surface CO2 efflux and its spatial and temporal variations in a young ponderosa pine plantation in northern California. Global Change Biology 7: 667-677.; Epron et al., 2004Epron, D.; Nouvellon, Y.; Roupsard, O.; Mouvondy, W.; Mabiala, A.; Saint-Andre, L.; Joffre, R.; Jourdan, J.; Bonnefond, J.M.; Berbigier, P.; Hamel, O. 2004. Spatial and temporal variations of soil respiration in a eucalyptus plantation in Congo. Forest Ecology and Management 202: 149-160., 2006Epron, D.; Bosc, A.; Bonal, D.; Freycon, V. 2006. Spatial variation of soil respiration across a topographic gradient in a tropical rain forest in French Guiana. Journal of Tropical Ecology 22: 565-574.; Kosugi et al., 2007Kosugi, Y.; Mitani, T.; Itoh, M.; Noguchi, S.; Tani, M.; Matsuo, N.; Takanashi, S.; Ohkubo, S.; Nik, A.R. 2007. Spatial and temporal variation in soil respiration in a southeast Asian tropical rainforest. Agricultural and Forest Meteorology 147: 35-47.; La Scala et al., 2010La Scala, N.; Mendonça, E.S.; Souza, J.J.; Panosso, A.R.; Simas, F.N.B.; Schaefer, C.E.G.R. 2010. Spatial and temporal variability in soil CO2-C emissions and relation to soil temperature at King George Island, Maritime Antarctica. Polar Science 4: 4479-487.; Leon et al., 2014Leon, E.; Vargas, R.; Bullock, S.; Lopez, E.; Panosso, A.R.; La Scala, N. 2014. Hot spots, hot moments, and spatio-temporal controls on soil CO2 efflux in a water-limited ecosystem. Soil Biology and Biochemistry 77: 12-21.), attributes with great influence on microbial activities that promote soil respiration.

The principal component analysis (PCA) of CO2 fluxes (Panosso et al., 2012Panosso, A.R.; Perillo, L.I.; Ferraudo, A.S.; Pereira, G.T.; Miranda, J.V.G.; La Scala, N. 2012. Fractal dimension and anisotropy of soil CO2 emission in a mechanically harvested sugarcane production area. Soil and Tillage Research 124: 8-16.) showed that water filled pore space, and total porosity and macroporosity were the main components to explain the variance of CO2 fluxes. Another study, about soil CO2 efflux in a water limited ecosystem (Leon et al., 2014Leon, E.; Vargas, R.; Bullock, S.; Lopez, E.; Panosso, A.R.; La Scala, N. 2014. Hot spots, hot moments, and spatio-temporal controls on soil CO2 efflux in a water-limited ecosystem. Soil Biology and Biochemistry 77: 12-21.), showed that the most important attributes were root biomass, soil volumetric water content and total porosity.

Mitigating CO2 fluxes in sugarcane cultivation still requires further studies aiming to assess their viability and enhancing their applicability for environmental purposes. More specifically, there is a need to study the main factors responsible for high soil CO2 fluxes, which can assist in the challenge of achieving stability of soil carbon through improved decision-making managements. This study aimed to evaluate CO2 fluxes and their relation to soil properties in sugarcane areas under different harvesting managements.

Materials and Methods

Experimental site

This study was conducted on a farm with more than 30 years of sugarcane (Saccharum spp.) cultivation history. The land belongs to a sugar and ethanol mill located in the Pradópolis, São Paulo State, Brazil (21°19’8” S, 48°7’24” W), approximately 500 m above sea level (Figure 1). The soil was classified as Haplustox (USDA Soil Taxonomy) (Latossolo Vermelho Eutroférrico, according to Brazilian Soil Classification System) with a clayey texture (561 g kg−1 to B, 517 g kg−1 to G-5 and 531 g kg−1 to G-10), and the topography of the area is flat and undulating. The regional climate is classified as B2rB’4a’ by the Thornthwaite system (Rolim et al., 2007Rolim, J.S.; Camargo, M.P.B.; Lania, D.G.; Moraes, J.F.F. 2007. Climatic classification of Koppen and Thornthwait systems their applicability in the determination of agroclimatic zonning for the state of São Paulo, Brazil. Bragantia 66: 711-720 (in Portuguese, with abstract in English).), indicating a mesothermal region with rainy summers and dry winters. The average precipitation is 1425 mm yr−1 and is concentrated between Oct and Mar. The average annual temperature over the last 30 years was 22.2 °C.

Figure 1
Description of experimental locations and relief maps with sampling grid details. B = burned sugarcane; G-5 = green sugarcane with 5 years of implementation; G-10 = green sugarcane with 10 years of implementation.

In 2011, three plots were chosen in areas with different systems and management times (Figure 1): the burned sugarcane (B) area has been managed under residue burning since the 1980s and the other areas were harvested under the green sugarcane system (G) with different starting times of green sugarcane adoption [5 years (G-5) that started in 2006 and another area with ten years (G-10) that started in 2001]. At the time of renewing the plantations, which occurred in every six ratoons in B and in G-10 in 2007) with mechanical removal of the ratoon of the previous crop and subsoiling to 0.45 m deep in the planting furrows. Afterward, 2 t ha−1 of dolomitic limestone and 480 kg ha−1 of NPK fertilizer at 10-25-20 formulation were also applied. On average, 100 m3 ha−1 of vinasse (by-product of biomass distillation of the sugarcane fuel industry) and 300 kg ha−1 of urea or 200 kg ha−1 of ammonium nitrate were applied to the areas after 5-7 months of the first fertilization.

In 2011-2012 (experimental evaluation period), treatment B with the sugarcane variety CTC4 (average maturity and high agricultural productivity) was in in its 5th ratoon with average yield of 67 t ha−1. Treatment G-5 with the planted variety RB85 5453 (early maturity, erect growth, high productivity with no limitation of soil water) was in its 4th ratoon with average yield of 80 t ha−1. Treatment G-10 with the sugarcane variety CTC 20 (early maturity, high tillering and high productivity along the cuts) was in its 5th ratoon with an average yield of 75 t ha−1. In this experiment, no manure or fertilizers were applied between the years 2010 and 2011 (before and during the field experiment) to control interferences of these factors on the CO2 fluxes. In each area, a sampling irregular grid of 1 ha was installed with 30 sampling points spaced at intervals with minimum of 2 m and maximum of 100 m. All points were georeferenced with the aid of a total station and a DGPS (Model L1/L2 Hiper Lite Plus).

Measurement of CO2 fluxes

Measurements of soil CO2 fluxes were simultaneously performed in the three sugarcane areas in the same period (10 d in Aug-Sept 2011) and on the same day time (7:00-11:00 a.m.) after harvesting, for standardization. For that, three portable systems (1 system/area) were used to monitor the changes in CO2 concentration inside the chamber using an infrared gas analyzer. The soil chamber has an internal volume of 854.2 cm3 with a circular soil contact area at the base of 83.7 cm2, which was placed on PVC collars previously inserted at each sampling point to 3 cm deep keeping is distant from the ratoon plant (approximately 30 cm) to decrease its influence on the CO2 fluxes. Once the chamber is set to the measurement mode, it takes around 1.5 min to run the time-change interpolation of CO2 concentration inside the chamber. The chambers were previously calibrated for this work.

Soil temperature (Ts) and soil water content (Ms) were measured simultaneously with CO2 concentration through a temperature sensor coupled with the system, and Ms was registered with a portable Hydrosense system.

Soil sampling and evaluation

For the microbial biomass (Biom) analysis, soil samples were collected at each point in the grid on the same day and time of CO2 measurement, but only for 2 d of each collection period (the first and last day of CO2 measurement) due to the large number of samples to be analyzed in 30 d (recommendation for the microbiological analysis). In the field, samples were kept in plastic bags inside Styrofoam boxes and transferred immediately to a refrigerator at 4 °C. The biomass analysis was performed according to the fumigation-extraction method proposed by Jenkinson and Powlson (1976)Jenkinson, D.S.; Powlson, D.S. 1976. The effects of biocidal treatments on metabolism in soil. V. Method for measuring soil biomass. Soil Biology and Biochemistry 8: 209-213..

For the other soil analysis, the samples were collected once at each point before the CO2 analysis. Disturbed soil samples were collected from the first 20 cm of soil to evaluate organic carbon (C) (Nelson and Sommers, 1982Nelson, D.W.; Sommers, L.E. 1982. Total C, organic C and OM. In: Page, R.H.; Kenny, D.R., eds. Methods of soil analysis. II. Chemical and microbiological properties. 2ed. Soil Science Society of America, Madison, WI, USA.), pH in CaCl2 and phosphorus (P) by resin procedure (Raij et al., 2001Raij, B. van; Andrade, J.C.; Cantarella, H.; Quaggio, J.A. 2001. Chemical Analysis to Evaluate the Fertility of Tropical Soils = Análise Química para Avaliação da Fertilidade de Solos Tropicais. Instituto Agronômico, Campinas, SP, Brazil (in Portuguese).), clay and mean weight diameter of soil aggregates (MWD).

Samples were exposed to air for 24 h, kept moist for aggregate preservation and then placed on a sieve set of 6.35 and 2 mm mesh diameter. Aggregates were obtained from samples retained by the 2 mm mesh, whereas those that passed through were again exposed to air until constant weight was achieved. Undisturbed soil samples were collected with aluminum rings and used to analyze macroporosity (Ma), microporosity (Mi) and bulk density (Bd). These physical analyses were carried out according to Brazilian Agricultural Research Corporation methodologies – Embrapa (1997).

Statistical analyses

Mean daily CO2 fluxes were evaluated by the t test for comparison between management areas (p < 0.05), using the program Minitab 14. These values were integrated to calculate the CO2 accumulated during 10 d.

Quantitative criteria of CO2 fluxes were defined by the distribution of CO2 data in each area (Table 1), defined as: very low (VL) fluxes, which included values lower than the first quartile (Q1); low fluxes (L), between Q1 and median values; moderate (M) fluxes, between median and third quartile (Q3); and high (H) fluxes, values greater than Q3.

Table 1
Summary of soil CO2 flux (µmol m−2 s−1) distribution statistics of burned and green cane areas.

This criterion was used to identify the influence of soil attributes on different CO2 concentrations, mainly by high fluxes and if the amount of soil attributes followed the same trend of CO2 criterion. When the values were different for the three sugarcane systems, discussion was made separately for each area.

The multivariate structure in the original data set was evaluated by the PCA that condensed the relevant information into a smaller set of orthogonal latent variables called principal components (PC-eigenvectors). Each pair of principal components (PCs) generates a two-dimensional representation of the original sample space, known as a biplot. The biplot explains the structure of variables directing beams of variable regions of maximum variability. In this work, we considered the principal components whose eigenvalues were greater than a unity (Kaiser, 1958Kaiser, H.F. 1958. The varimax criterion for analytic rotation in factor analysis. Psychometrika 23: 178-200.). The sign and relative size of the linear function coefficients, which define the PC scores were used as an indication of the weight to be assigned to each variable in the different experimental plots (Johnson and Wichern, 2002Johnson, R.A.; Wichern, D.W. 2002. Applied Multivariate Statistical Analysis. 5ed. Prentice Hall, Upper Saddle River, NJ, USA.). The correlation between soil attributes with PCs to explain the management types were compared with the mean values of soil CO2 fluxes.

Results and Discussion

CO2 total fluxes

Considering the CO2 total fluxes, G-10 showed higher values (mean 2.71 µmol CO2 m−2 s−1), representing a significant difference (p < 0.05) of 28 % compared with G-5 (1.93 µmol CO2 m−2 s−1) and 41 % compared with B (1.58 µmol CO2 m−2 s−1) (Table 1). The G-5 and B did show statistical difference, the G-5 area is in a transition stage, considering the recent conversion to the green sugarcane system. This effect can be seen in Figure 2 that shows the CO2 total emission accumulation in the three management systems.

Figure 2
Accumulated soil CO2 emission on soil during Aug-Sept 2011 in burned sugarcane (B), green harvest sugarcane for 5 years (G-5) and 10 years (G-10).

Most CO2 fluxes in G-10 may be associated with greater microbial activity in areas with major plant residue deposition on soil surface. Minimum soil tillage, like the green sugarcane management, provides favorable conditions for the development of microorganisms in the soil surface layer, which increases microbial biomass and CO2 production (Matias et al., 2009).

Biom results showed similar trends of fluxes in the three experimental areas (Table 2), with higher values of Biom falling in the high and moderate CO2 flux groups and lower values in the low and very low CO2 flux groups. This indicates a direct participation of the microbial biomass in CO2 production during soil organic matter (SOM) decomposition (Jenkinson and Ladd, 1981Jenkinson, D.S.; Ladd, J.N. 1981. Microbial biomass in soil: measurement and turnover. Soil Biology and Biochemistry 5: 415-471.). However, this process is not always favorable for storing soil carbon, and for some authors, the reduction in SOM can be a result of CO2 fluxes (Cerri et al., 2007Cerri, C.E.P.; Sparoveki, G.; Bernoux, M.; Easterling, W.E.; Melillo, J.M.; Cerri, C.C. 2007. Tropical agriculture and global warming: impacts and mitigation options. Scientia Agricola 64: 83-99.).

Table 2
Descriptive statistics of soil microbiological, physical and chemical attributes across experimental areas in accordance to CO2 flux criterion (high, moderate, low and very low).

The physical and chemical soil attributes showed no clear relation with the different groups of CO2 fluxes, with the exception of macro- and microporosity, where macroporosity was the soil attribute of high frequency in all three areas, mainly to explain the high CO2 fluxes group (Figures 3A, B, C). This can be attributed to gas transport in the soil, because according to Fick's gas diffusion Law, macroporosity provides better conductivity for the CO2 molecule in the soil, facilitating gas fluxes (Alvenäs and Jansson, 1997Alvenäs, G.; Jansson, P.E. 1997. Model for evaporation, moisture and temperature of bare soil: calibration and sensitivity analysis. Agricultural and Forest Meteorology 88: 47-56.; Brito et al., 2009Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83.). In turn, microporosity provides a more irregular path hindering CO2 fluxes in the soil. Thus, G-10 presented greater macroporosity than B and G-5 (Table 2), meaning that despite greater bulk density in G-10 due the mechanized traffic, soil porosity did not impair the fluxes compared to B and this aspect can be attributed to the straw left on the soil that promotes more soil aggregation and porosity.

Figure 3
Two-dimensional representation of the principal components 1 and 2 (biplot) in areas of B (A), G-5 (B) and G-10 (C), with the description of high (H), moderate (Md), low (L) and very low (VL) CO2 fluxes. Biom = microbial biomass; Ms = Soil water content; Ts = soil temperature; MWD = mean weight diameter; Bd = bulk density; Ma = macroporosity; Mi = microporosity; C = organic carbon content; V% = base saturation; P = phosphorus.

The PCA results showed that the first two principal components, PC1 and PC2, explained respectively 50 and 30 % of the variance for all areas and jointly was responsible for more than 80 % of the variance. A similar result was found in a study by Panosso et al. (2011)Panosso, A.R.; Marques Júnior, J.; Milori, D.M.B.P.; Ferraudo, A.S.; Barbieri, M.; Pereira, G.T.; La Scala, N. 2011. Soil CO2emission and its relation to soil properties in sugarcane areas under Slash-and-burn and Green harvest. Soil and Tillage Research 111: 190-196. on CO2 fluxes, where the PCs together explained 70 % of the variability of soil attributes (physical and chemical), with PC1 explaining 52 % and PC2, 18 %. This means that the soil attributes included in the two principal components are sufficient to explain the CO2 flux variations in the soil. This is because the soil attributes used in this study promote the CO2 flux, such as porosity that makes gas transportation in the soil viable (Xu and Qi, 2001Xu, M.; Qi, Y. 2001. Soil-surface CO2 efflux and its spatial and temporal variations in a young ponderosa pine plantation in northern California. Global Change Biology 7: 667-677.; Kosugi et al., 2007Kosugi, Y.; Mitani, T.; Itoh, M.; Noguchi, S.; Tani, M.; Matsuo, N.; Takanashi, S.; Ohkubo, S.; Nik, A.R. 2007. Spatial and temporal variation in soil respiration in a southeast Asian tropical rainforest. Agricultural and Forest Meteorology 147: 35-47.; Brito et al., 2009Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83.) and the microbiological attribute that produces CO2 by microbial respiration during OM decomposition increasing the CO2 flux (Fang et al., 1998Fang, C.; Moncrieff, J.B.; Gholz, H.L.; Clark, K.L. 1998. Soil CO2efflux and its spatial variation in a Florida slash pine plantation. Plant and Soil 205: 135-146.).

Burned sugarcane

In the burned area, the attributes contributing most to PC1 by order of influence represented by the correlation coefficient were Bd (-0.99), Biom (-0.97) and Mi (0.94) (Table 3). Bd and Biom influenced the low CO2 fluxes (mean 1.48 µmol CO2 m−2 s−1) (Figure 3A), Bd described 15 % of the variability and Biom in 14 %. The positive and negative correlation could indicate that in places with low bulk density and microbial biomass, there was a greater incidence of low CO2 fluxes (Figure 3A), reinforcing the relation between biomass and CO2, in areas where biomass was low, there were more low CO2 fluxes. This is because the microorganisms promote the CO2 flux, as cited previously.

Table 3
Variance data of the principal components PC1 and PC2 with correlation and ranking of importance of the microbiological, physical and chemical soil attributes.

Bulk density influences soil porosity in general, increasing Mi, and the prevalence of more Mi than Ma can hinder gas transportation in the soil and the emission to the surface, resulting in more low category of CO2 fluxes. This effect can be confirmed by the Mi analysis that described 13 % of the variability in very low CO2 fluxes (mean 0.96 µmol CO2 m−2 s−1) (Figure 3A), because Mi hinders the soil gas circulation through the less rectilinear and more irregular paths, diminishing high CO2 fluxes and promoting very low CO2 fluxes.

The PC2 showed that the attributes explaining most of the variance were Ma (-0.91), C (0.84) and Ms (-0.78). Ms explained 14 % of the high CO2 flux class (2.11 µmol CO2 m−2 s−1) (Figure 3A). Similar results were found by Ryu et al. (2009)Ryu, S.; Concilio, A.; Chen, J.; North, M.; Ma, S. 2009. Prescribed burning and mechanical thinning effects on belowground conditions and soil respiration in a mixed-conifer forest, California. Forest Ecology Management 257: 1324-1332. in soils in California (U.S.A.), where Ms explained 14 % of the CO2 flux variability and showed a negative correlation with CO2. Epron et al. (2006)Epron, D.; Bosc, A.; Bonal, D.; Freycon, V. 2006. Spatial variation of soil respiration across a topographic gradient in a tropical rain forest in French Guiana. Journal of Tropical Ecology 22: 565-574. also found a negative correlation between CO2 and Ms in a study on CO2 fluxes from forest soils in French Guiana.

Still, the negative relationship between soil respiration and soil water content contrasted with results that highlighted soil moisture controlling temporal soil respiration (Panosso et al., 2008Panosso, A.R.; Pereira, G.T.; Marques Junior, J.M.; La Scala, N. 2008. Spatial variability of CO2 emission on Oxisol soils cultivated with sugarcane under different management practices = Variabilidade espacial da emissão de CO2 em Latossolos sob cultivo de cana-de-açúcar em diferentes sistemas de manejo. Engenharia Agrícola 28: 227-236 (in Portuguese, with abstract in English).; Maier et al., 2010Maier, M.; Schack-Kirchner, H.; Hildebrand, E.E.; Holst, J. 2010. Pore-space CO2 dynamics in a deep, well-aerated soil. European Journal of Soil Science 61: 877-887.; Goutal et al., 2012Goutal, N.; Parent, F.; Bonnaud, P.; Demaison, J.; Nourisson, G.; Epron, D.; Ranger, J. 2012. Soil CO2 concentration and efflux as affected by heavy traffic in forest in northeast France. Europan Journal of Soil Science 63: 261-271.), but not spatial variation and, in our study, only the spatial variability of CO2 was analyzed, which explained the non-direct effect of soil moisture on the CO2 flux.

Soil C content showed a positive correlation with PC2 and an opposite trend with Ma for the group high CO2 fluxes (Figure 3A), which suggests that in places with high CO2 fluxes, the C trend is decreased, that is, more fluxes and less C storage (Cerri et al., 2007Cerri, C.E.P.; Sparoveki, G.; Bernoux, M.; Easterling, W.E.; Melillo, J.M.; Cerri, C.C. 2007. Tropical agriculture and global warming: impacts and mitigation options. Scientia Agricola 64: 83-99.). A similar result was found by Panosso et al. (2012)Panosso, A.R.; Perillo, L.I.; Ferraudo, A.S.; Pereira, G.T.; Miranda, J.V.G.; La Scala, N. 2012. Fractal dimension and anisotropy of soil CO2 emission in a mechanically harvested sugarcane production area. Soil and Tillage Research 124: 8-16. where the CO2 results showed a positive correlation with PC2 (0.77) and negative with carbon stock (-0.31). Intense OM decomposition tends to consume the C available in the soil with increasing CO2 released by microorganisms. On the other hand, low organic carbon content can be understood as protected and stabilized inside microaggregates (Lenka and Lal, 2013Lenka, N.K.; Lal, R. 2013. Soil aggregation and greenhouse gas flux after 15 years of wheat straw and fertilizer management in a no-till system. Soil and Tillage Research 126: 78-89.). Moreover, corroborating the results of our study, Fang et al. (1998)Fang, C.; Moncrieff, J.B.; Gholz, H.L.; Clark, K.L. 1998. Soil CO2efflux and its spatial variation in a Florida slash pine plantation. Plant and Soil 205: 135-146. detected more CO2 associated with the low C content in pine soils.

Green sugarcane with 5 years

For the G-5 treatment, the attributes with greater correlation to PC1 were Ma (-0.95), Ts (0.93), and clay (-0.85) (Table 3). Ma and clay were grouped in the high CO2 class (2.78 µmol CO2 m−2 s−1) (Figure 3B), where the Ma explained 13 % and clay 11 % of variance. Panosso et al. (2011)Panosso, A.R.; Marques Júnior, J.; Milori, D.M.B.P.; Ferraudo, A.S.; Barbieri, M.; Pereira, G.T.; La Scala, N. 2011. Soil CO2emission and its relation to soil properties in sugarcane areas under Slash-and-burn and Green harvest. Soil and Tillage Research 111: 190-196. showed correlation of −0.73 between clay and PC1 in a study of CO2 fluxes, with greater clay in the green than in the burned cane, however, the CO2 showed more significance in PC2, indicating little interaction of clay with CO2.

A possible explanation of negative correlation of clay with PC1 to explain the high CO2 flux is that clay promotes a type of carbon protection in the soil, that is, the adsorption of OM with mineral particles (mainly clay minerals and oxides) protects OM from microbial decomposition and prevents C loss as CO2, however, if the clay content is low, as shown in our study, protection is smaller, promoting more high CO2 flux situations.

Soil temperature Ts explained 13 % of the variance in low CO2 fluxes (mean of 1.66 µmol CO2 m−2 s−1) for the G-5 treatment. It is justifiable because soil temperature in G-5 was lower than B and G-10 and low temperature can promote low CO2 fluxes due the slow microorganism activity. The great performance of soil microorganisms occurred around 30 °C (Kononova, 1975Kononova, M.M. 1975. Humus of virgin and cultivated soils. In: Gieseking, J.E., ed. Soil components. Springer, Berlin, Germany.) and in G-5, soil temperature was 18 °C (Table 2). The correlation between CO2 and Ts was also found in studies of Carbonell-Bojollo et al. (2012)Carbonell-Bojollo, R.; Torres, M.A.R.R.; Rodriguez-Lizana, A.; Ordónez-Fernández, R. 2012. Influence of soil and climate conditions on CO2 emissions from agricultural soils. Water Air and Soil Pollution 223: 3425-3435., Lenka and Lal (2013)Lenka, N.K.; Lal, R. 2013. Soil aggregation and greenhouse gas flux after 15 years of wheat straw and fertilizer management in a no-till system. Soil and Tillage Research 126: 78-89., Shrestha et al. (2013)Shrestha, R.K.; Lal, R.; Rimal, B. 2013. Soil carbon fluxes and balances and soil properties of organically amended no-till corn production systems. Geoderma 197-198: 117-185. and Song et al. (2013)Song, Z.; Yuan, H.; Kimberley, M.O.; Jiang, H.; Zhou, G.; Wang, H. 2013. Soil CO2 flux dynamics in the two main plantation forest types in subtropical China. Science of the Total Environment 444: 363-368..

In PC2, the attributes that showed higher correlation were V (-0.95), Biom (-0.95) and Ms (0.86). The V and Biom were grouped in the very low CO2 flux class (mean 1.27 µmol CO2 m−2 s−1) (Figure 3B), indicated by the negative correlation coefficient, with places of low V and Biom with more incidences of very low CO2 fluxes. This is because low base saturation and soil acidity affected the soil microbial activity resulting in lower CO2 fluxes.

Green sugarcane with 10 years

The attributes that mostly contributed to the explanation of PC1 on the G-10 were, in order of influence, P (-0.97), pH (-0.93) and MWD (-0.91) (Table 3). In addition, we observed that pH and MWD influenced the high CO2 fluxes group (mean 4.02 µmol CO2 m−2 s−1) in 14 % and 13 % respectively, with negative correlations with PC1. This indicates that the greater incidence of high CO2 fluxes can be explained by the low values of pH and MWD.

The pH values ranged from 4-5 (Table 2), probably due to the more intense OM decomposition than in the other areas due the greater amount of straw that stimulates microbial decomposition and this process may decrease the pH during the nitrification stage. Xu and Qi (2001)Xu, M.; Qi, Y. 2001. Soil-surface CO2 efflux and its spatial and temporal variations in a young ponderosa pine plantation in northern California. Global Change Biology 7: 667-677. showed negative correlation of CO2 emission with the pH in a study on spatial variation of soil CO2 fluxes.

MWD is associated with the physical protection of OM, and soil aggregates play this role by preventing the release of occluded carbon that serves as a source of energy for the microbial biomass. Thus, the negative correlation between MWD with PC1, mainly to explain the high CO2 fluxes, helps to understand that lower MWD can promote less C protection and, thus, high CO2 fluxes.

Some variation (15 %) of CO2 fluxes within very low CO2 (1.56 µmol CO2 m−2 s−1) was explained by the P content, with a negative correlation with PC1. This indicates that the increased amount of P in the G-10 area influenced the smaller incidence of very low fluxes. The P content stimulates the production of the phosphatase enzyme produced by specific phosphate solubilizing microorganisms (Barroso and Nahas, 2006Barroso, C.B.; Nahas, E. 2006. Solubilization of iron phosphate by free or immobilized pellets and spores of Aspergillus niger. Research Journal of Microbiology 1: 210-219.), resulting in greater CO2 by microorganisms during decomposition, thus, explaining the smaller incidence of very low CO2 fluxes.

PC2 presented a greater explanation by the attributes Ma (-0.99), Bd (0.97) and C (-0.76). The Ma trend was the same in B and G-5 areas in which high CO2 fluxes were explained by Ma (Table 3). Panosso et al. (2012)Panosso, A.R.; Perillo, L.I.; Ferraudo, A.S.; Pereira, G.T.; Miranda, J.V.G.; La Scala, N. 2012. Fractal dimension and anisotropy of soil CO2 emission in a mechanically harvested sugarcane production area. Soil and Tillage Research 124: 8-16. studied CO2 soil fluxes in sugarcane management and also found significant correlation of PC1 with CO2 (0.77) and with Ma (0.75).

In a study by Leon et al. (2014)Leon, E.; Vargas, R.; Bullock, S.; Lopez, E.; Panosso, A.R.; La Scala, N. 2014. Hot spots, hot moments, and spatio-temporal controls on soil CO2 efflux in a water-limited ecosystem. Soil Biology and Biochemistry 77: 12-21., the PCA showed that the principal soil attribute responsible for High CO2 fluxes season was root biomass. In our study, Ma was always present and explained the significant variance of high CO2 flux, despite the negative correlation with PC1 (Figure 3B) and PC2 (Figures 3A, C). Ma explained 19 % in B, 13 % in G-5 and 23 % in G-10 of high CO2 fluxes.

Ma has an important relationship with soil CO2 fluxes, as the greater number of macropores enables soil gas circulation (Brito et al., 2009Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83.), furthermore, an increased number of Ma enables greater concentrations of soil O2, which stimulates the activity of microbial decomposition and consequent soil CO2 fluxes. In a study by Goutal et al. (2012)Goutal, N.; Parent, F.; Bonnaud, P.; Demaison, J.; Nourisson, G.; Epron, D.; Ranger, J. 2012. Soil CO2 concentration and efflux as affected by heavy traffic in forest in northeast France. Europan Journal of Soil Science 63: 261-271., changes in soil macroporosity percentages affected plant roots and associated microbial activities. Thus, soil Ma and Mi influenced possible flux trajectories of soil gases, which affected O2 and CO2 fluxes (Brito et al., 2009Brito, L.F.; Marques Júnior, J.; Pereira, G.T.; Souza, Z.M. 2009. Soil CO2 emission of sugarcane fields as affected by topography. Scientia Agricola 66: 77-83.). According to the Fick's law (Alvenäs and Jansson, 1997Alvenäs, G.; Jansson, P.E. 1997. Model for evaporation, moisture and temperature of bare soil: calibration and sensitivity analysis. Agricultural and Forest Meteorology 88: 47-56.), the relations between Ma and CO2 are controlled by several factors including total porosity, soil water content and tortuosity coefficient.

Other soil attributes interpreted in isolation can cause double interpretation, for example, Bd and C were attributes that presented both positive and negative correlations with the principal components (Table 3). A study of Panosso et al. (2011)Panosso, A.R.; Marques Júnior, J.; Milori, D.M.B.P.; Ferraudo, A.S.; Barbieri, M.; Pereira, G.T.; La Scala, N. 2011. Soil CO2emission and its relation to soil properties in sugarcane areas under Slash-and-burn and Green harvest. Soil and Tillage Research 111: 190-196. concluded that the bulk density associated with the humification index relates better than other properties with soil CO2 emission, as this property is the most important to understand the emission variability in the area of burned cane.

In some studies, CO2 and C showed positive correlations (La Scala et al., 2000La Scala, N.; Marques Júnior, J.; Pereira, G.T.; Corá, J.E. 2000. Carbon dioxide emission related to chemical properties of a tropical bare soil. Soil Biology and Biochemistry 32: 1469-1473.; Lenka and Lal, 2013Lenka, N.K.; Lal, R. 2013. Soil aggregation and greenhouse gas flux after 15 years of wheat straw and fertilizer management in a no-till system. Soil and Tillage Research 126: 78-89.; Medeiros et al., 2011Medeiros, J.C.; Silva, A.P.; Cerri, C.E.P.; Fracetto, F.J.C. 2011. Linking physical quality and CO2 emission under long-term no-till and conventional-till in a subtropical soil in Brazil. Plant and Soil 338: 5-15.) mainly related to the supply of the substrate to microbial activity. Negative correlations (Fang et al., 1998Fang, C.; Moncrieff, J.B.; Gholz, H.L.; Clark, K.L. 1998. Soil CO2efflux and its spatial variation in a Florida slash pine plantation. Plant and Soil 205: 135-146.) associated with the limitation of decomposition due to adverse soil and climate conditions have also been observed, although their influence was not always significant (Epron et al., 2004Epron, D.; Nouvellon, Y.; Roupsard, O.; Mouvondy, W.; Mabiala, A.; Saint-Andre, L.; Joffre, R.; Jourdan, J.; Bonnefond, J.M.; Berbigier, P.; Hamel, O. 2004. Spatial and temporal variations of soil respiration in a eucalyptus plantation in Congo. Forest Ecology and Management 202: 149-160.). According to Song et al. (2013)Song, Z.; Yuan, H.; Kimberley, M.O.; Jiang, H.; Zhou, G.; Wang, H. 2013. Soil CO2 flux dynamics in the two main plantation forest types in subtropical China. Science of the Total Environment 444: 363-368., the increase in CO2 fluxes associated with soil carbon is complex and may involve both positive and negative feedbacks. This requires further studies of the CO2 flow and soil carbon dynamics.

Conclusions

The harvesting of green sugarcane presented higher CO2 total fluxes than the burned sugarcane did. This effect is associated with greater microbial activity in areas with greater plant waste deposition on the soil surface. On the other hand, the CO2 fluxes based on high-low criteria showed that macroporosity explained the "high" CO2 fluxes, this is because the greater number of macropores improved soil gas circulation and enabled greater concentrations of soil O2, which stimulate the activity of microbial decomposition and consequent soil CO2 fluxes.

Acknowledgments

To the São Paulo State Foundation for Research Support (FAPESP – 2010/18.979-5; 2011/04.842-0) for financial support and to the São Martinho ethanol mill for providing the study area.

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Publication Dates

  • Publication in this collection
    Nov-Dec 2016

History

  • Received
    23 Apr 2015
  • Accepted
    21 Dec 2015
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